Thought Leadership
The Shopify CEO, who once made AI usage mandatory, now sees a growing problem: employees are passing along unrefined, AI-generated work to colleagues without reviewing it.
Just about a year ago, Tobias Lütke was among the most vocal advocates of AI in everyday work. The co-founder and CEO of Shopify CEO implements AI-first approach to staffing decisions declared the use of such tools a basic prerequisite for his workforce at the time: anyone wanting to request additional staff had to first demonstrate that the task could not be solved even with AI support. In a recent interview, he sounds quite different.
When AI Results Are Passed Along Unverified
On the podcast “The Knowledge Project,” Lütke spoke about a development that is now causing friction within the company. An internal term has already taken hold for the habit of passing along unverified AI results to colleagues: “We call them slop grenades that people throw at each other,” he said. He added that this was “definitely not a good thing.”
As an example, Lütke cited emails: AI is actually supposed to help summarize points rather than turning them into, as he called it, “a big treatise” that ultimately helps no one. He described the outcome as follows: “You don’t even really read it, and then it has to be checked by colleagues who then say, that doesn’t look right.” In short, people are letting AI do the work for them, he concluded.
Researchers Quantify the Follow-up Costs
A dedicated technical term has now established itself in research for low-quality AI outputs that appear professional on the surface. Consulting firm BetterUp Labs, together with Stanford University’s Social Media Lab, investigated the phenomenon in a survey of 962 full-time office workers in the US. Over half of the participants admitted to having passed along such low-quality results themselves, particularly often where companies actively encourage AI usage. Over a third stated that they had been on the receiving end, quantifying the additional effort required for corrections at an average of 3.4 hours per month.
Cited examples included formally flawless emails with non-functional links or unnecessarily complex programming code. The key point according to the study: unlike typically poor human work, such outputs appear well-founded at first glance, even though they lack substantive content.
The survey also highlights consequences for team collaboration. Colleagues suspected of sending such content were rated by respondents as less capable and less pleasant to work with. More than a third of affected respondents declared that they would prefer not to work with those individuals in the future.
Compared to the previous year, the required effort has increased noticeably. In 2025, 40 percent of respondents had reported similar issues, with an average correction effort of two hours. At the time, costs were estimated at 186 US dollars per month per employee, which, extrapolated to a company with 10,000 employees, resulted in a potential annual productivity loss of up to 9 million US dollars.
(Editorial Team)
